Design requirements, student perception indicators and validation metrics for intelligent exploratory learning environments

  • Authors:

  • Manolis Mavrikis;Sergio Gutierrez-Santos;Eirini Geraniou;Richard Noss

  • Affiliations:

  • London Knowledge Lab, Institute of Education, University of London, London, UK;London Knowledge Lab, Computer Science and Information Systems, Birkbeck, University of London, London, UK;London Knowledge Lab, Institute of Education, University of London, London, UK;London Knowledge Lab, Institute of Education, University of London, London, UK

  • Venue:
  • Personal and Ubiquitous Computing
  • Year:
  • 2013

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Abstract

The new forms of interaction afforded by innovative technology and open-ended environments provide promising opportunities for exploratory learning. Exploratory environments, however, require appropriate support to lead to meaningful learning outcomes. This paper focuses on the design and validation of intelligent exploratory environments. The goal is twofold: requirements that guide the operationalisation of pedagogical strategies to computer-based support and methodology for the validation of the system. As designers, we need to understand what kind of interaction is conducive to learning and aligned with the theoretical principles behind exploratory learning. We summarise this in the form of three requirements--rare interruption of interaction, co-location of feedback and support towards specific goals. Additionally, developing intelligent systems requires many resources and a long time to build. To facilitate their evaluation, we define three indicators-- helpfulness, repetitiveness and comprehension--of students' perception of the intelligent system and three metrics--relevance, coverage, and scope--which allow the identification of design or implementation problems at various phases of the development. The paper provides a case study with a mathematical microworld that demonstrates how the three requirements are taken into account in the design of the user-facing components of the system and outline the methodology for formative validation of the intelligent support.